What are AI Agents?
AI Agents are specialized AI assistants with custom instructions (prompts) that help you:- Enforce coding standards and best practices
- Follow specific architectural patterns
- Generate code in a particular style
- Handle domain-specific tasks
- Automate repetitive workflows
- They have their own context window
Creating AI Agents
Personal Agents
Personal agents are available only to you across all your projects. To create a personal agent:- Main Sidebar > Agents
- Click “New”
-
Fill in the agent details:
- Name: A descriptive name (e.g., “flutter-best-practices”)
- Description: What this agent does
- Prompt: Detailed instructions for the AI
- Click “Save”
Team Agents
Team agents are shared across all members of your team and team projects. To create a team agent:- Navigate to your Team Settings
- Go to Agents section
- Click “New”
- Configure the agent (same fields as personal agents)
- Click “Save”
Note: Team agents take precedence over personal agents in team projects.
Agent Configuration
Writing Effective Prompts
A good agent prompt should:- Be Specific: Clearly define the agent’s purpose
- Include Examples: Show desired output format
- Set Constraints: Define what to do and what to avoid
- Establish Context: Explain the project type and requirements
Example Agent Prompts
Flutter Clean Architecture Agent:Using Agents in Your Workspace
Automatic Agent Loading
When you create a new sandbox, Teta automatically:- Fetches your personal or team agents
- Creates YAML configuration files in the file system
- Makes agents available to the AI
Agent File Structure
Agents are stored as YAML files:Agent Best Practices
1. Keep Agents Focused
Each agent should have a single, clear purpose:- ✅ “Database Migration Generator”
- ❌ “Do Everything Agent”
2. Use Multiple Agents
Create specialized agents for different tasks:- Architecture Agent: Enforces project structure
- Testing Agent: Generates tests
- Documentation Agent: Creates comprehensive docs
- Refactoring Agent: Improves existing code
3. Iterate and Improve
Monitor how your agents perform:- Review generated code quality
- Update prompts based on results
- Add more specific instructions over time
- Remove unnecessary constraints
4. Share Knowledge
For teams:- Document agent purposes
- Share successful prompts
- Create a library of proven agents
- Establish team standards through agents
Common Agent Use Cases
1. Code Style Enforcement
2. Framework-Specific Guidelines
3. Documentation Generation
4. Testing Standards
Advanced Features
Conditional Logic
Agents can include conditional behavior:Context Awareness
Agents can reference project state:Troubleshooting
Agent Not Working
Symptoms: Agent instructions aren’t being followed Solutions:- Check agent YAML file in
.claude/agents/ - Verify prompt is clear and specific
- Ensure agent name is properly formatted
- Try restarting the sandbox
Conflicting Agents
Symptoms: AI gives inconsistent responses Solutions:- Review all active agents
- Check for contradictory instructions
- Consolidate similar agents
- Use more specific agent names
Agent Files Not Loading
Symptoms: Changes to agents don’t appear Solutions:- Verify Teta has your agents
- Check sandbox logs for errors
- Restart the development machine
Example: Complete Agent Setup
Here’s a real-world example for a Flutter e-commerce project:1. Project Standards Agent
2. API Agent
3. UI Agent
Conclusion
AI Agents are powerful tools for standardizing your development workflow and ensuring consistent, high-quality code generation. Start with a few focused agents and expand as you identify patterns in your work.Related Documentation
- Getting Started - Platform basics
- MCP Servers - Extend functionality
- GitHub Integration - Version control
Need help with agents? Contact support@teta.so